Inovasi Desain Rumah Apung Sebagai Solusi Adaptif Penanggulangan Banjir Rob Di Permukiman Pesisir Kelurahan Karangsari Kabupaten Kendal Provinsi Jawa Tengah
Bibliographic record
Abstract
Wilayah RW 5 Kelurahan Karangsari, Kabupaten Kendal, Jawa Tengah merupakan kawasan pesisir yang terdampak banjir rob secara berkala, menyebabkan kerusakan fisik pada rumah warga dan menurunkan kualitas hidup masyarakat. Permasalahan ini membutuhkan solusi adaptif yang sesuai dengan karakteristik lingkungan setempat. Penelitian ini menawarkan inovasi desain rumah apung sebagai bentuk adaptasi terhadap banjir rob yang kian intens. Metode yang digunakan meliputi survei lapangan untuk mengidentifikasi kondisi eksisting rumah, analisis kerentanan terhadap banjir rob, serta diskusi partisipatif dengan masyarakat guna menggali kebutuhan dan aspirasi lokal. Hasil kegiatan ini menghasilkan rancangan desain rumah apung berbasis modular dengan sistem pondasi drum terapung dan struktur ringan tahan air, yang disesuaikan dengan pola hidup masyarakat pesisir. Penerapan desain ini berpotensi mengurangi kerusakan akibat banjir rob serta meningkatkan kenyamanan dan keamanan tempat tinggal. Dampak kegiatan ini dirasakan oleh mitra berupa peningkatan pengetahuan, kesadaran adaptasi terhadap perubahan iklim, dan peluang untuk mewujudkan permukiman yang lebih berkelanjutan di masa depan.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.016 | 0.004 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".